Artificial Intelligence and Finance: A bibliometric review on the Trends, Influences, and Research Directions [version 1; peer review: 2 approved]
Background This bibliometric study examines the intersection of artificial intelligence (AI) and finance, providing a comprehensive analysis of its evolution, central themes, and avenues for further exploration. The study aims to uncover the theoretical foundations, methodological approaches, and pr...
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| Format: | Article |
| Language: | English |
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F1000 Research Ltd
2025-01-01
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| Online Access: | https://f1000research.com/articles/14-122/v1 |
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| author | Pankaj Kumar Tyagi Biswajit Ghose Prasenjit Roy Asokan Vasudevan Premendra Kumar Singh |
| author_facet | Pankaj Kumar Tyagi Biswajit Ghose Prasenjit Roy Asokan Vasudevan Premendra Kumar Singh |
| author_sort | Pankaj Kumar Tyagi |
| collection | DOAJ |
| description | Background This bibliometric study examines the intersection of artificial intelligence (AI) and finance, providing a comprehensive analysis of its evolution, central themes, and avenues for further exploration. The study aims to uncover the theoretical foundations, methodological approaches, and practical implications of AI in financial contexts. Methods The research employs bibliometric techniques, using 607 Web of Science (WoS) indexed papers. The Theory-Context-Characteristics-Methodology (TCCM) framework guides the analysis, focusing on thematic mapping to explore key topics. Core areas such as risk management, market efficiency, and innovation are analyzed, alongside emerging themes like ethical AI, finance applications, and factors influencing AI-driven financial decision-making. Results The findings reveal critical gaps in interdisciplinary methods, ethical considerations, and methodological advancements necessary to develop robust and transparent AI systems. Thematic mapping highlights the increasing importance of ethical AI practices and the influence of AI on financial decision-making processes. Emerging research areas emphasize the need for innovative frameworks and solutions to address current challenges. Conclusions This study provides valuable insights for academics, industry practitioners, and policymakers to harness transformative potential of AI in finance. This research offers a foundation for future studies and practical applications by addressing key gaps and promoting interdisciplinary and ethical approaches in a rapidly evolving field. |
| format | Article |
| id | doaj-art-6a0989b20858452aa73bd75c7f6ca277 |
| institution | Kabale University |
| issn | 2046-1402 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | F1000 Research Ltd |
| record_format | Article |
| series | F1000Research |
| spelling | doaj-art-6a0989b20858452aa73bd75c7f6ca2772025-02-05T01:00:04ZengF1000 Research LtdF1000Research2046-14022025-01-0114176927Artificial Intelligence and Finance: A bibliometric review on the Trends, Influences, and Research Directions [version 1; peer review: 2 approved]Pankaj Kumar Tyagi0Biswajit Ghose1Prasenjit Roy2Asokan Vasudevan3https://orcid.org/0000-0002-9866-4045Premendra Kumar Singh4https://orcid.org/0000-0002-6627-4560Chandigarh University, Mohali, Punjab, IndiaDepartment of Commerce, Tezpur University, Napaam, Assam, IndiaDepartment of Commerce, Tezpur University, Napaam, Assam, IndiaFaculty of Business and Communications, INTI International University, Nilai, Negeri Sembilan, MalaysiaCentre for Distance and Online Education, Sharda University, Greater Noida, Uttar Pradesh, IndiaBackground This bibliometric study examines the intersection of artificial intelligence (AI) and finance, providing a comprehensive analysis of its evolution, central themes, and avenues for further exploration. The study aims to uncover the theoretical foundations, methodological approaches, and practical implications of AI in financial contexts. Methods The research employs bibliometric techniques, using 607 Web of Science (WoS) indexed papers. The Theory-Context-Characteristics-Methodology (TCCM) framework guides the analysis, focusing on thematic mapping to explore key topics. Core areas such as risk management, market efficiency, and innovation are analyzed, alongside emerging themes like ethical AI, finance applications, and factors influencing AI-driven financial decision-making. Results The findings reveal critical gaps in interdisciplinary methods, ethical considerations, and methodological advancements necessary to develop robust and transparent AI systems. Thematic mapping highlights the increasing importance of ethical AI practices and the influence of AI on financial decision-making processes. Emerging research areas emphasize the need for innovative frameworks and solutions to address current challenges. Conclusions This study provides valuable insights for academics, industry practitioners, and policymakers to harness transformative potential of AI in finance. This research offers a foundation for future studies and practical applications by addressing key gaps and promoting interdisciplinary and ethical approaches in a rapidly evolving field.https://f1000research.com/articles/14-122/v1Artificial Intelligence Finance Bibliometric Analysis TCCM Thematic Mappingeng |
| spellingShingle | Pankaj Kumar Tyagi Biswajit Ghose Prasenjit Roy Asokan Vasudevan Premendra Kumar Singh Artificial Intelligence and Finance: A bibliometric review on the Trends, Influences, and Research Directions [version 1; peer review: 2 approved] F1000Research Artificial Intelligence Finance Bibliometric Analysis TCCM Thematic Mapping eng |
| title | Artificial Intelligence and Finance: A bibliometric review on the Trends, Influences, and Research Directions [version 1; peer review: 2 approved] |
| title_full | Artificial Intelligence and Finance: A bibliometric review on the Trends, Influences, and Research Directions [version 1; peer review: 2 approved] |
| title_fullStr | Artificial Intelligence and Finance: A bibliometric review on the Trends, Influences, and Research Directions [version 1; peer review: 2 approved] |
| title_full_unstemmed | Artificial Intelligence and Finance: A bibliometric review on the Trends, Influences, and Research Directions [version 1; peer review: 2 approved] |
| title_short | Artificial Intelligence and Finance: A bibliometric review on the Trends, Influences, and Research Directions [version 1; peer review: 2 approved] |
| title_sort | artificial intelligence and finance a bibliometric review on the trends influences and research directions version 1 peer review 2 approved |
| topic | Artificial Intelligence Finance Bibliometric Analysis TCCM Thematic Mapping eng |
| url | https://f1000research.com/articles/14-122/v1 |
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